DeepPlanner4Cardio: an automatic multi-view planning tool for CMR
Motivation: Manual planning of the 4 standard cardiac views (2-chamber, 3-chamber, 4-chamber, short axis) is currently a time-consuming process that demands significant operator interaction and expertise. Goal(s): Our aim is to streamline and automate this process to reduce examination times and minimize dependency on highly trained operators. Approach: We developed DeepPlanner4Cardio, a deep learning model designed to predict the standard cardiac views simultaneously. Results: DeepPlanner4Cardio achieved a clinically acceptable accuracy of 94% on the test set with a mean orientation error of 11º and a mean displacement error of 5.9 mm, both within the inter-operator variability ranges. Impact: DeepPlanner4Cardio effectively supports CMR operators by providing an accessible, automated solution to enable fast and reproducible cardiac view planning, demonstrating great potential to be applied in a clinical setting.
Authors
- Markus Henningsson (ORCID: https://orcid.org/0000-0001-6142-3005)
- Pedro Osório
- Rita Nunes (ORCID: https://orcid.org/0000-0001-8271-6579)
- Teresa Correia (ORCID: https://orcid.org/0000-0002-1606-9550)
- João de Deus Gomes dos Santos (ORCID: https://orcid.org/0000-0003-1113-3178)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/1966
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00